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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

3-D Modeling of the CFR Engine for the Investigation of Knock on Natural Gas

Abstract: Engine knock and misfire are barriers to pathways leading to higher efficiency natural gas (NG) engines, where the general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by low emissions limits and the wide range of chemical reactivity in pipeline quality NG, making the understanding of fuel- engine interactions essential to achieving high efficiencies in spark-ignited NG engines. The present work highlights a three-dimensional computational fluid dynamics (CFD) model of the Cooperative Fuel Research (CFR) engine to investigate knock behavior when running on NG. Using a Converge CFD model of the CFR engine fuel-engine interactions that lead to knock with NG, including effects of fuel reactivity, engine operating parameters, and exhaust gas recirculation, are being investigated. A GT-Power model is used to estimate appropriate initial conditions in the Converge CFD model, including cylinder wall, piston, valves, and port surface temperatures as well as residual gas fraction. In order to validate the model, in-cylinder pressure data taken with a CFR engine is compared to model predictions while varying compression ratio, CA50, and BMEP.

CFR Engine, Converge CFD, knock, Natural Gas↗
NASA NTRS1924

Effect of altitude on power of aviation engines

These notes are intended to furnish practical and general data on the effect of altitude on engine power. The effective horsepower of an engine is a function of the mean pressure of the fluid acting on the pistons, of the R.P.M. of the engine and of the mechanical efficiency.

ENGINES - PERFORMANCE↗
NASA NTRS2016

Thermal Propulsion Capture System Heat Exchanger Design

One of the biggest challenges of manned spaceflight beyond low earth orbit and the moon is harmful radiation that astronauts would be exposed to on their long journey to Mars and further destinations. Using nuclear energy has the potential to be a more effective means of propulsion compared to traditional chemical engines (higher specific impulse). An upper stage nuclear engine would allow astronauts to reach their destination faster and more fuel efficiently. Testing these engines poses engineering challenges due to the need to totally capture the engine exhaust. The Thermal Propulsion Capture System is a concept for cost effectively and safely testing Nuclear Thermal Engines. Nominally, hydrogen exhausted from the engine is not radioactive, but is treated as such in case of fuel element failure. The Thermal Propulsion Capture System involves injecting liquid oxygen to convert the hydrogen exhaust into steam. The steam is then cooled and condensed into liquid water to allow for storage. The Thermal Propulsion Capture System concept for ground testing of a nuclear powered engine involves capturing the engine exhaust to be cooled and condensed before being stored. The hydrogen exhaust is injected with liquid oxygen and burned to form steam. That steam must be cooled to saturation temperatures before being condensed into liquid water. A crossflow heat exchanger using water as a working fluid will be designed to accomplish this goal. Design a cross flow heat exchanger for the Thermal Propulsion Capture System testing which: Eliminates the need for water injection cooling, Cools steam from 5800 F to saturation temperature, and Is efficient and minimizes water requirement.

Richard, Evan M.↗
DOE OSTI2024

The Case for Reducing Emissions from Heavy-Duty Off-Road Applications via Ducted Fuel Injection

Designers of heavy-duty diesel engines use a variety of techniques to improve efficiency and reduce pollutant emissions. Ducted fuel injection (DFI), high fuel injection pressures, optimized injection orifices, multiple injection sites, and oxygenated fuels are a few techniques used by designers to improve fuel/charge-gas mixtures within the combustion chamber to improve efficiency and emissions results. Ducted fuel injection (DFI) has been proven to substantially reduce soot for low- and mid-load conditions in heavy duty engines, without significantly increasing nitrogen oxides (NO x ). This study investigates the performance of DFI utilizing conventional diesel fuel and the potential the technique has for future research utilizing varieties of test fuels and operating parameter values. Optimization for high engine efficiency and low emissions will help facilitate DFI deployment for substantial environmental benefits in heavy-duty sectors where electrification and/or carbon-free fuels aren’t feasible.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Flight Deck Design of a Hybrid Turbine/Electric Aircraft

The SUbsonic Single Aft eNgine (SUSAN) program is being developed as a sustainable subsonic regional aircraft. NASA is conducting trade studies for this future hybrid single aisle passenger aircraft. The goal of reducing emission levels by 50% will be enabled through an advanced design. An aft mounted single turbine engine provides thrust and electric power to drive 16 wing mounted electric engines. Using the 16 counter-rotating electric fans will create an efficient, very high bypass ratio, engine. Electric engines allow for distributed thrust, reducing control surfaces and provide a greater dynamic response. Batteries provide boost for takeoff and climb, allowing a smaller, more efficient, turbine engine. As part of the SUSAN effort, two pilot-in-the-loop studies were conducted at NASA Langley Research Center in Virginia to explore flight deck design issues. In particular: how many throttles are required/desired for a 17-engine aircraft, does the hybrid electric design change the answer, what are the requirements for electric engine displays, what system pages are required, and what information is required to monitor the batteries. Objective and subjective data were collected after each scenario and at the end of the day with a guided set of questionnaires from sixteen crews paired by airline. Data along with pilot comments were used to improve the throttle and engine displays between the studies and used to make the final recommendations on flight deck configurations. This paper provides final design recommendations for the SUSAN flight deck and justification for each recommendation.

PAI↗
NASA NTRS2014

Numerical Simulation of Boundary Layer Ingesting (BLI) Inlet-Fan Interaction

Future civil transport designs may incorporate engine inlets integrated into the body of the aircraft to take advantage of efficiency increases due to weight and drag reduction. Additional increases in engine efficiency are predicted if the inlet ingests the lower momentum boundary layer flow. Previous studies have shown, however, that efficiency benefits of Boundary Layer Ingesting (BLI) ingestion are very sensitive to the magnitude of fan and duct losses, and blade structural response to the non-uniform flow field that results from a BLI inlet has not been studied in-depth. This paper presents an effort to extend the modeling capabilities of an existing rotating turbomachinery unsteady analysis code to include the ability to solve the external and internal flow fields of a BLI inlet. The TURBO code has been a successful tool in evaluating fan response to flow distortions for traditional engine/inlet integrations, such as the development of rotating stall and inlet distortion through compressor stages. This paper describes the first phase of an effort to extend the TURBO model to calculate the external and inlet flowfield upstream of fan so that accurate pressure distortions that result from BLI configurations can be computed and used to analyze fan aerodynamics and structural response. To validate the TURBO program modifications for the BLI flowfield, experimental test data obtained by NASA for a flushmounted S-duct with large amounts of boundary layer ingestion was modeled. Results for the flow upstream and in the inlet are presented and compared to experimental data for several high Reynolds number flows to validate the modifications to the solver. Quantitative data is presented that indicates good predictive capability of the model in the upstream flow. A representative fan is attached to the inlet and results are presented for the coupled inlet/fan model. The impact on the total pressure distortion at the AIP after the fan is attached is examined.

Inlet Fan Interactions↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗
NASA NTRS2023

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be easily expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗
DOE OSTI2019

Engineering Charge-Transfer States for Efficient, Low-Energy-Loss Organic Photovoltaics

Charge transfer (CT) between donors and acceptors following photoexcitation of organic photovoltaics (OPVs) gives rise to bound electron–hole pairs across the donor–acceptor interface, known as CT states. Although these states are essential to charge separation, they are also a source of energy loss. As a result of reduced overlap between electron and hole wavefunctions, CT states are influenced by details of the film morphology and molecular structure. In this work, we describe several important strategies for tuning the energy level and dynamics of the CT state and approaches that can enhance their dissociation efficiency into free charges. Furthermore, we provide an overview of recent physical insights into the key parameters that significantly reduce the Frenkel-to-CT energy offset and recombination energy losses while preserving a high charge-generation yield. Our analysis leads to critical morphological and molecular design strategies for achieving efficient, low-energy-loss OPVs.

14 SOLAR ENERGY↗
DOE OSTI2019

Pore environment engineering in metal–organic frameworks for efficient ethane/ethylene separation

Selective adsorption of trace amounts of C 2 H 6 from bulk C 2 H 4 is a significantly important and extremely challenging task in industry, which requires an adsorbent with specific pore properties. In this work, we describe a strategy for adjusting the pore environment of metal–organic frameworks (MOFs) by introducing different amounts of methyl groups in the channel to enhance the guest–host interaction between C 2 H 6 and the framework. To prove this concept, 2,3,5,6-tetramethylterephthalic acid (TMBDC) was deliberately added to a microporous MOF, Ni(BDC)(DABCO) 0.5 , affording a series of mixed-ligand materials, Ni(BDC) 1– x (TMBDC) x (DABCO) 0.5 ( x = 0, 0.2, 0.45, 0.71, 1), having different pore environments. Significantly, these mixed-ligand materials demonstrated improved performance in terms of the adsorption capacity of C 2 H 6 and C 2 H 4 with an unprecedented C 2 H 6 uptake of 2.21 mmol g –1 for Ni(TMBDC)(DABCO) 0.5 at 0.0625 bar and 298 K. With the best theoretical C 2 H 6 /C 2 H 4 selectivity predicted by IAST, Ni(TMBDC)(DABCO) 0.5 exhibited effective separation of C 2 H 6 /C 2 H 4 (1/15, v/v) and great recyclability in five consecutive adsorption/desorption cycles throughout the breakthrough experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1979

Multivariable control altitude demonstration on the F100 turbofan engine

The control system designed under the Multivariable Control Synthesis (MVCS) program for the F100 turbofan engine is described. The MVCS program, applied the linear quadratic regulator (LQR) synthesis methods in the design of a multivariable engine control system to obtain enhanced performance from cross-coupled controls, maximum use of engine variable geometry, and a systematic design procedure that can be applied efficiently to new engine systems. Basic components of the control system, a reference value generator for deriving a desired equilibrium state and an approximate control vector, a transition model to produce compatible reference point trajectories during gross transients, gain schedules for producing feedback terms appropriate to the flight condition, and integral switching logic to produce acceptable steady-state performance without engine operating limit exceedance are described and the details of the F100 implementation presented. The engine altitude test phase of the MVCS program, and engine responses in a variety of test operating points and power transitions are presented.

Lehtinen, B.↗
NASA NTRS1981

The supersonic fan engine: An advanced concept in supersonic cruise propulsion

Engine performance and mission studies were carried out for turbofan engines equipped with supersonic through-flow fans. The mission was for a commercial supersonic transport with a Mach 2.32 capability. The advantages of the supersonic fan engines are discussed in terms of mission range comparisons with other engine types. The effects of fan efficiency, inlet losses, and engine weight on engine performance and mission range are shown. The range of a supersonic transport with supersonic fan engines could be 10 to 20 percent better than with other types having the same technology core.

Franciscus, L. C.↗
NASA NTRS1993

Engine Would Recover Exhaust Energy More Efficiently

Exhaust energy used for supercharging and extra shaft power. Flow of exhaust apportioned by waste gate to meet demand of turbocharger, and portion not fed to turbocharger sent to power-recovery turbine. Expected to increase fuel efficiency.

Dimpelfeld, Philip M.↗
NASA NTRS2004

Thermal and Environmental Barrier Coatings for Advanced Propulsion Engine Systems

Ceramic thermal and environmental barrier coatings (TEBCs) are used in gas turbine engines to protect engine hot-section components in the harsh combustion environments, and extend component lifetimes. For future high performance engines, the development of advanced ceramic barrier coating systems will allow these coatings to be used to simultaneously increase engine operating temperature and reduce cooling requirements, thereby leading to significant improvements in engine power density and efficiency. In order to meet future engine performance and reliability requirements, the coating systems must be designed with increased high temperature stability, lower thermal conductivity, and improved thermal stress and erosion resistance. In this paper, ceramic coating design and testing considerations will be described for high temperature and high-heat-flux engine applications in hot corrosion and oxidation, erosion, and combustion water vapor environments. Further coating performance and life improvements will be expected by utilizing advanced coating architecture design, composition optimization, and improved processing techniques, in conjunction with modeling and design tools.

Zhu, Dong-Ming↗